A Network Analysis of the Relationship Between Automation and Job Characteristics

Abstract

The purpose of this study is to identify core occupational characteristics that affect the potential for a job to be automated and to reveal the relationship and paths between those characteristics, such as skill(s), work environment and knowledge. In this study, a network was estimated and visualised to identify the relationship between occupational characteristics using the Gaussian graphical model method and to reveal the occupational characteristics linked to the potential for automation variable. As a result of estimating and visualising the network, it was found that the occupational characteristics with low potential for automation were art, decision-making, assisting and caring for others and working in cramped spaces, while those with high potential for automation involved repeating the same tasks. Furthermore, after analysing the shortest paths from each occupational characteristic node to the automation node, it was revealed that even occupational characteristics with high potential for automation can have varying levels of automation possibility depending on the mediators. Based on the results, education and vocational training policies for low- and middle-skill workers, young workers and potential workers are suggested.